Cervical Cancer Detection System Analysis by Segmentation Methods

Authors

  • M. Robinson Joel  Department of CSE, SMK Fomra Institute of Technology, India
  • G. Gandhi Jabakumar  Department of CSE, SMK Fomra Institute of Technology, India
  • D. Pradeep Kumar  Department of CSE, SMK Fomra Institute of Technology, India

Keywords:

Papanicolaou (Pap), PET, MAP.

Abstract

Cancer has been materialized to be paramount health issues of humanity. One of the prevalent types of cancer is cervical cancer and The Papanicolaou (Pap) test or Pap smear is the elementary test for cervical screening and it holds the microscopic examination of cervical cells collected from the cervix. As manual interpretation is laborious, unobjective, time-consuming process with extensive deviations in diagnosis among experts. Manual analysis comprises conventional cytology of biopsy sample or Pap smear. The accuracy of the Pap test is influenced by the two dominant factors: sampling error where diagnostic cell does not fall onto the slide, the other being interpretation error caused by inexperienced lab technicians.

References

  1. Youyi S, Ee-Leng T, & Xudong, J 2017, 'Accurate Cervical Cell segmentation from Overlapping Clumps in Pap Smear Images', IEEE Transactions on Medical Imaging, vol.36, no.1,pp. 288-300
  2. Savas T, Cumhur T, H, Fatih, I, 2015, 'Advances in Nanotechnology and micro fluidics for human Papillomavirus diagnostics', Proceedings of the IEEE vol.103, no.2,pp.161 - 178
  3. Wei M, Zhe, C, & Wei S 2015, 'A Segmentation Algorithm for Quantitative Analysis of Heterogeneous Tumors of the Cervix With 18 F-FDG PET/CT', IEEE Transactions on Biomedical Engineering, vol.62, no.10,pp.2465-2479.
  4. Chao L, Sudhakar C, & David A. J, 2012, 'Simultaneous Non rigid Registration, Segmentation, and Tumor Detection in MRI Guided Cervical Cancer Radiation Therapy', IEEE Transactions on Medical Imaging, vol.31,no.6, pp. 1213 - 1227
  5. Amir A, Hayit G, & Jacob G 2010, 'Automated and Interactive Lesion Detection and Segmentation in Uterine Cervix Images', IEEE Transactions on Medical Imaging,vol.29,n0.2,pp.488-501
  6. Yeshwanth S, Enrique C, Brian N 2009, 'A Unified Model-Based Image Analysis Framework for Automated Detection of Precancerous Lesions in Digitized Uterine Cervix Images', IEEE Journal of Selected Topics in Signal Processing, vol. 3, no. 1, pp. 101-111.
  7. Yinhai W, Danny C, & Osama S, E 2009, 'Assisted Diagnosis of Cervical Intraepithelial Neoplasia (CIN)', IEEE Journal of Selected Topics in Signal Processing, vol. 3,no. 1,pp. 112-121

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Published

2017-02-28

Issue

Section

Research Articles

How to Cite

[1]
M. Robinson Joel, G. Gandhi Jabakumar, D. Pradeep Kumar, " Cervical Cancer Detection System Analysis by Segmentation Methods, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 1, pp.571-574, January-February-2017.